About
Ervin Dervishaj is a PhD Fellow at the Machine Learning Section of the Department of Computer Science, University of Copenhagen. His research spans theoretical and applied machine learning, with a focus on recommendation systems, medical imaging, and computational modeling.
The Machine Learning Section engages in interdisciplinary work across
- Information retrieval
- Medical data analysis
- Remote sensing
- Sustainability
- Biological data modeling
Recent publications highlight expertise in
- Recommendation system interpretability (2025)
- GAN-based collaborative filtering (2022)
- Linguistic typology through language embeddings (2018)
- Medical imaging applications in osteoarthritis and neurodegenerative diseases (2016-2018)
- Optimization algorithms for adversarial learning (2016-2017)
He contributes to projects involving the SCIENCE AI Centre and the TreeSense Centre for remote sensing applications.
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